Abstract
An Optical Character Recognition (OCR) of “Aksara Lontara” has been constructed using a novel combination of feature extraction methods in this study. The ancient font of “Lontara” is then translated into Bahasa Indonesia to help non-native language to learn this language. Two powerful extraction feature methods, i.e., Modified Direction Feature (MDF) and Fourier Descriptor (FD) are stages combined to deal with two dominant phases of the Lontara font. The classification process is conducted using Support Vector Machine (SVM) as a fast and straightforward learning method deal with 23 fonts in image containing of 150×120 pixels. In this research, 50 verbs were used for training and 30 verbs for validating the system. The results show that system can reach 96% accuracy using this hybrid in extraction feature with kernel variable of C = 3 and σ = 8.
Highlights
One of a great and most implemented field in pattern recognitions is Optical Character Recognition (OCR) which can transform images into a script for further processing by computers (Mori et al, 1992)
Several researchers have engaged in developing an OCR for aksara lontara through assimilating image processing techniques and artificial intelligence
The training process is applied to get the best parameters of the feature values which is obtained by the extraction process of Modified Direction Feature (MDF) and Fourier Descriptor (FD) methods
Summary
One of a great and most implemented field in pattern recognitions is Optical Character Recognition (OCR) which can transform images into a script for further processing by computers (Mori et al, 1992). Several researchers have engaged in developing an OCR for aksara lontara through assimilating image processing techniques and artificial intelligence. It has been completed for specific characters and classification purposes only using Backpropagation Neural Network (Alwi and Wardoyo, 2010). Authors proposed a hybrid feature extraction, MDF and FD methods, for a translation system of “Aksara Lontara” based on image script. This is a uniqueness of this article.
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